diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index 8e851a8e8..117278585 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -360,13 +360,14 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date', value_col: str = 'profit_ratio' - ) -> Tuple[float, pd.Timestamp, pd.Timestamp]: + ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]: """ Calculate max drawdown and the corresponding close dates :param trades: DataFrame containing trades (requires columns close_date and profit_ratio) :param date_col: Column in DataFrame to use for dates (defaults to 'close_date') :param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio') - :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time + :return: Tuple (float, highdate, lowdate, highvalue, lowvalue) with absolute max drawdown, + high and low time and high and low value. :raise: ValueError if trade-dataframe was found empty. """ if len(trades) == 0: @@ -382,7 +383,10 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date' raise ValueError("No losing trade, therefore no drawdown.") high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col] low_date = profit_results.loc[idxmin, date_col] - return abs(min(max_drawdown_df['drawdown'])), high_date, low_date + high_val = max_drawdown_df.loc[max_drawdown_df.iloc[:idxmin] + ['high_value'].idxmax(), 'cumulative'] + low_val = max_drawdown_df.loc[idxmin, 'cumulative'] + return abs(min(max_drawdown_df['drawdown'])), high_date, low_date, high_val, low_val def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]: diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index dde0f8dd2..5b3f813f2 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -322,14 +322,20 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], result['strategy'][strategy] = strat_stats try: - max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown( + max_drawdown, _, _, _, _ = calculate_max_drawdown( results, value_col='profit_ratio') + drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown( + results, value_col='profit_abs') strat_stats.update({ 'max_drawdown': max_drawdown, + 'max_drawdown_abs': drawdown_abs, 'drawdown_start': drawdown_start, 'drawdown_start_ts': drawdown_start.timestamp() * 1000, 'drawdown_end': drawdown_end, 'drawdown_end_ts': drawdown_end.timestamp() * 1000, + + 'max_drawdown_low': low_val, + 'max_drawdown_high': high_val, }) csum_min, csum_max = calculate_csum(results) @@ -341,6 +347,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], except ValueError: strat_stats.update({ 'max_drawdown': 0.0, + 'max_drawdown_abs': 0.0, + 'max_drawdown_low': 0.0, + 'max_drawdown_high': 0.0, 'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc), 'drawdown_start_ts': 0, 'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc), @@ -471,6 +480,12 @@ def text_table_add_metrics(strat_results: Dict) -> str: strat_results['stake_currency'])), ('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), + ('Max Drawdown', round_coin_value(strat_results['max_drawdown_abs'], + strat_results['stake_currency'])), + ('Max Drawdown high', round_coin_value(strat_results['max_drawdown_high'], + strat_results['stake_currency'])), + ('Max Drawdown low', round_coin_value(strat_results['max_drawdown_low'], + strat_results['stake_currency'])), ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)), ('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)), ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"), diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py index 4325e537e..682c2b018 100644 --- a/freqtrade/plot/plotting.py +++ b/freqtrade/plot/plotting.py @@ -145,7 +145,7 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame, Add scatter points indicating max drawdown """ try: - max_drawdown, highdate, lowdate = calculate_max_drawdown(trades) + max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades) drawdown = go.Scatter( x=[highdate, lowdate], diff --git a/freqtrade/plugins/protections/max_drawdown_protection.py b/freqtrade/plugins/protections/max_drawdown_protection.py index d54e6699b..d1c6b192d 100644 --- a/freqtrade/plugins/protections/max_drawdown_protection.py +++ b/freqtrade/plugins/protections/max_drawdown_protection.py @@ -55,7 +55,7 @@ class MaxDrawdown(IProtection): # Drawdown is always positive try: - drawdown, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit') + drawdown, _, _, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit') except ValueError: return False, None, None diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index 3c4687745..555808679 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -274,15 +274,17 @@ def test_create_cum_profit1(testdatadir): def test_calculate_max_drawdown(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) - drawdown, h, low = calculate_max_drawdown(bt_data) + drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(bt_data) assert isinstance(drawdown, float) assert pytest.approx(drawdown) == 0.21142322 - assert isinstance(h, Timestamp) - assert isinstance(low, Timestamp) - assert h == Timestamp('2018-01-24 14:25:00', tz='UTC') - assert low == Timestamp('2018-01-30 04:45:00', tz='UTC') + assert isinstance(hdate, Timestamp) + assert isinstance(lowdate, Timestamp) + assert isinstance(hval, float) + assert isinstance(lval, float) + assert hdate == Timestamp('2018-01-24 14:25:00', tz='UTC') + assert lowdate == Timestamp('2018-01-30 04:45:00', tz='UTC') with pytest.raises(ValueError, match='Trade dataframe empty.'): - drawdown, h, low = calculate_max_drawdown(DataFrame()) + drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(DataFrame()) def test_calculate_csum(testdatadir): @@ -310,13 +312,16 @@ def test_calculate_max_drawdown2(): # sort by profit and reset index df = df.sort_values('profit').reset_index(drop=True) df1 = df.copy() - drawdown, h, low = calculate_max_drawdown(df, date_col='open_date', value_col='profit') + drawdown, hdate, ldate, hval, lval = calculate_max_drawdown( + df, date_col='open_date', value_col='profit') # Ensure df has not been altered. assert df.equals(df1) assert isinstance(drawdown, float) # High must be before low - assert h < low + assert hdate < ldate + # High value must be higher than low value + assert hval > lval assert drawdown == 0.091755 df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_date'])